{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MeanReversion backtest with Portfolio Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the chapter 04, we introduced `zipline` to simulate the computation of alpha factors from trailing cross-sectional market, fundamental, and alternative data. \n",
    "\n",
    "Now we will exploit the alpha factors to derive and act on buy and sell signals using the custom MeanReversion factor developed in the last chapter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using Zipline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook uses the `conda` environnment `ml4t-zipline`.\n",
    "\n",
    "Please follow the instructions provided [here](../../installation)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:07.968478Z",
     "start_time": "2020-06-17T19:06:07.966392Z"
    }
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:08.941883Z",
     "start_time": "2020-06-17T19:06:07.972349Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "from pytz import UTC\n",
    "import logbook\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from zipline import run_algorithm\n",
    "from zipline.api import (attach_pipeline,\n",
    "                         date_rules,\n",
    "                         time_rules,\n",
    "                         order_target_percent,\n",
    "                         pipeline_output,\n",
    "                         record, schedule_function,\n",
    "                         get_open_orders,\n",
    "                         calendars,\n",
    "                         set_commission, \n",
    "                         set_slippage)\n",
    "from zipline.finance import commission, slippage\n",
    "from zipline.pipeline import Pipeline, CustomFactor\n",
    "from zipline.pipeline.factors import Returns, AverageDollarVolume\n",
    "\n",
    "from pypfopt.efficient_frontier import EfficientFrontier\n",
    "from pypfopt import risk_models\n",
    "from pypfopt import expected_returns\n",
    "\n",
    "from pyfolio.utils import extract_rets_pos_txn_from_zipline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:08.948973Z",
     "start_time": "2020-06-17T19:06:08.943654Z"
    }
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Logging Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:08.961171Z",
     "start_time": "2020-06-17T19:06:08.950498Z"
    }
   },
   "outputs": [],
   "source": [
    "# setup stdout logging\n",
    "zipline_logging = logbook.NestedSetup([\n",
    "    logbook.NullHandler(level=logbook.DEBUG),\n",
    "    logbook.StreamHandler(sys.stdout, level=logbook.INFO),\n",
    "    logbook.StreamHandler(sys.stderr, level=logbook.ERROR),\n",
    "])\n",
    "zipline_logging.push_application()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algo Settings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:08.969023Z",
     "start_time": "2020-06-17T19:06:08.963304Z"
    }
   },
   "outputs": [],
   "source": [
    "# Settings\n",
    "MONTH = 21\n",
    "YEAR = 12 * MONTH\n",
    "N_LONGS = 50\n",
    "N_SHORTS = 50\n",
    "VOL_SCREEN = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:08.977768Z",
     "start_time": "2020-06-17T19:06:08.971263Z"
    }
   },
   "outputs": [],
   "source": [
    "start = pd.Timestamp('2013-01-01', tz=UTC)\n",
    "end = pd.Timestamp('2017-01-01', tz=UTC)\n",
    "capital_base = 1e7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mean Reversion Factor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:08.996318Z",
     "start_time": "2020-06-17T19:06:08.979186Z"
    }
   },
   "outputs": [],
   "source": [
    "class MeanReversion(CustomFactor):\n",
    "    \"\"\"Compute ratio of latest monthly return to 12m average,\n",
    "       normalized by std dev of monthly returns\"\"\"\n",
    "    inputs = [Returns(window_length=MONTH)]\n",
    "    window_length = YEAR\n",
    "\n",
    "    def compute(self, today, assets, out, monthly_returns):\n",
    "        df = pd.DataFrame(monthly_returns)\n",
    "        out[:] = df.iloc[-1].sub(df.mean()).div(df.std())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Pipeline created by the `compute_factors()` method returns a table with a long and a short column for the 25 stocks with the largest negative and positive deviations of their last monthly return from its annual average, normalized by the standard deviation. It also limited the universe to the 500 stocks with the highest average trading volume over the last 30 trading days. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:09.005279Z",
     "start_time": "2020-06-17T19:06:08.997847Z"
    }
   },
   "outputs": [],
   "source": [
    "def compute_factors():\n",
    "    \"\"\"Create factor pipeline incl. mean reversion,\n",
    "        filtered by 30d Dollar Volume; capture factor ranks\"\"\"\n",
    "    mean_reversion = MeanReversion()\n",
    "    dollar_volume = AverageDollarVolume(window_length=30)\n",
    "    return Pipeline(columns={'longs'  : mean_reversion.bottom(N_LONGS),\n",
    "                             'shorts' : mean_reversion.top(N_SHORTS),\n",
    "                             'ranking': mean_reversion.rank(ascending=False)},\n",
    "                    screen=dollar_volume.top(VOL_SCREEN))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before_trading_start() ensures the daily execution of the pipeline and the recording of the results, including the current prices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:09.015817Z",
     "start_time": "2020-06-17T19:06:09.006905Z"
    }
   },
   "outputs": [],
   "source": [
    "def before_trading_start(context, data):\n",
    "    \"\"\"Run factor pipeline\"\"\"\n",
    "    context.factor_data = pipeline_output('factor_pipeline')\n",
    "    record(factor_data=context.factor_data.ranking)\n",
    "    assets = context.factor_data.index\n",
    "    record(prices=data.current(assets, 'price'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set up Rebalancing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The new rebalance() method submits trade orders to the exec_trades() method for the assets flagged for long and short positions by the pipeline with equal positive and negative weights. It also divests any current holdings that are no longer included in the factor signals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:09.025071Z",
     "start_time": "2020-06-17T19:06:09.016862Z"
    }
   },
   "outputs": [],
   "source": [
    "def exec_trades(data, positions):\n",
    "    \"\"\"Place orders for assets using target portfolio percentage\"\"\"\n",
    "    for asset, target_percent in positions.items():\n",
    "        if data.can_trade(asset) and not get_open_orders(asset):\n",
    "            order_target_percent(asset, target_percent)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimize Portfolio Weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:09.033197Z",
     "start_time": "2020-06-17T19:06:09.026160Z"
    }
   },
   "outputs": [],
   "source": [
    "def optimize_weights(prices, short=False):\n",
    "\n",
    "    returns = expected_returns.mean_historical_return(prices=prices,\n",
    "                                                      frequency=252)\n",
    "\n",
    "    cov = risk_models.sample_cov(prices=prices, \n",
    "                                 frequency=252)\n",
    "\n",
    "    # get weights that maximize the Sharpe ratio\n",
    "    ef = EfficientFrontier(expected_returns=returns,\n",
    "                           cov_matrix=cov,\n",
    "                           weight_bounds=(0, 1),\n",
    "                           gamma=0)\n",
    "\n",
    "    ef.max_sharpe()\n",
    "    if short:\n",
    "        return {asset: -weight for asset, weight in ef.clean_weights().items()}\n",
    "    else:\n",
    "        return ef.clean_weights()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:09.044134Z",
     "start_time": "2020-06-17T19:06:09.034231Z"
    }
   },
   "outputs": [],
   "source": [
    "def rebalance(context, data):\n",
    "    \"\"\"Compute long, short and obsolete holdings; place orders\"\"\"\n",
    "\n",
    "    factor_data = context.factor_data\n",
    "    assets = factor_data.index\n",
    "\n",
    "    longs = assets[factor_data.longs]\n",
    "    shorts = assets[factor_data.shorts]\n",
    "\n",
    "    divest = context.portfolio.positions.keys() - longs.union(shorts)\n",
    "    exec_trades(data, positions={asset: 0 for asset in divest})\n",
    "\n",
    "    # get price history\n",
    "    prices = data.history(assets, fields='price',\n",
    "                          bar_count=252+1, # for 1 year of returns \n",
    "                          frequency='1d')\n",
    "\n",
    "    if len(longs) > 0:\n",
    "        long_weights = optimize_weights(prices.loc[:, longs])\n",
    "        exec_trades(data, positions=long_weights)\n",
    "    if len(shorts) > 0:\n",
    "        short_weights = optimize_weights(prices.loc[:, shorts], short=True)\n",
    "        exec_trades(data, positions=short_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Backtest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `rebalance()` method runs according to `date_rules` and `time_rules` set by the `schedule_function()` utility at the beginning of the week, right after market_open as stipulated by the built-in US_EQUITIES calendar (see docs for details on rules). \n",
    "\n",
    "You can also specify a trade commission both in relative terms and as a minimum amount. There is also an option to define slippage, which is the cost of an adverse change in price between trade decision and execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:06:09.055856Z",
     "start_time": "2020-06-17T19:06:09.045090Z"
    }
   },
   "outputs": [],
   "source": [
    "def initialize(context):\n",
    "    \"\"\"Setup: register pipeline, schedule rebalancing,\n",
    "        and set trading params\"\"\"\n",
    "    attach_pipeline(compute_factors(), 'factor_pipeline')\n",
    "    schedule_function(rebalance,\n",
    "                      date_rules.week_start(),\n",
    "                      time_rules.market_open(),\n",
    "                      calendar=calendars.US_EQUITIES)\n",
    "\n",
    "    set_commission(us_equities=commission.PerShare(cost=0.00075, min_trade_cost=.01))\n",
    "    set_slippage(us_equities=slippage.VolumeShareSlippage(volume_limit=0.0025, price_impact=0.01))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Algorithm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The algorithm executes upon calling the run_algorithm() function and returns the backtest performance DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:10:15.283176Z",
     "start_time": "2020-06-17T19:06:09.057106Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2020-06-17 19:06:09.283495] WARNING: Loader: Refusing to download new benchmark data because a download succeeded at 2020-06-17 19:06:04.481769+00:00.\n",
      "[2020-06-17 19:06:09.305700] WARNING: Loader: Refusing to download new treasury data because a download succeeded at 2020-06-17 19:06:05.197769+00:00.\n",
      "[2020-06-17 19:06:39.998649] INFO: Performance: after split: asset: Equity(189 [AOS]), amount: 62678, cost_basis: 36.54, last_sale_price: 79.9\n",
      "[2020-06-17 19:06:39.999088] INFO: Performance: returning cash: 0.0\n",
      "[2020-06-17 19:06:52.630873] INFO: Performance: after split: asset: Equity(2086 [OGE]), amount: -16942, cost_basis: 35.11, last_sale_price: 68.06\n",
      "[2020-06-17 19:06:52.631270] INFO: Performance: returning cash: 0.0\n",
      "[2020-06-17 19:07:23.453324] INFO: Performance: after split: asset: Equity(869 [DSW]), amount: -1398, cost_basis: 42.38, last_sale_price: 87.44\n",
      "[2020-06-17 19:07:23.453727] INFO: Performance: returning cash: 0.0\n",
      "[2020-06-17 19:09:14.752739] INFO: Performance: after split: asset: Equity(406 [BOFI]), amount: 52116, cost_basis: 22.25, last_sale_price: 83.29\n",
      "[2020-06-17 19:09:14.753153] INFO: Performance: returning cash: 0.0\n",
      "[2020-06-17 19:10:15.263419] INFO: zipline.finance.metrics.tracker: Simulated 1008 trading days\n",
      "first open: 2013-01-02 14:31:00+00:00\n",
      "last close: 2016-12-30 21:00:00+00:00\n"
     ]
    }
   ],
   "source": [
    "backtest = run_algorithm(start=start,\n",
    "                         end=end,\n",
    "                         initialize=initialize,\n",
    "                         before_trading_start=before_trading_start,\n",
    "                         bundle='quandl',\n",
    "                         capital_base=capital_base)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:10:15.293681Z",
     "start_time": "2020-06-17T19:10:15.285090Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 1008 entries, 2013-01-02 21:00:00+00:00 to 2016-12-30 21:00:00+00:00\n",
      "Data columns (total 39 columns):\n",
      "algo_volatility            1007 non-null float64\n",
      "algorithm_period_return    1008 non-null float64\n",
      "alpha                      1007 non-null float64\n",
      "benchmark_period_return    1008 non-null float64\n",
      "benchmark_volatility       1007 non-null float64\n",
      "beta                       1007 non-null float64\n",
      "capital_used               1008 non-null float64\n",
      "ending_cash                1008 non-null float64\n",
      "ending_exposure            1008 non-null float64\n",
      "ending_value               1008 non-null float64\n",
      "excess_return              1008 non-null float64\n",
      "factor_data                1008 non-null object\n",
      "gross_leverage             1008 non-null float64\n",
      "long_exposure              1008 non-null float64\n",
      "long_value                 1008 non-null float64\n",
      "longs_count                1008 non-null int64\n",
      "max_drawdown               1008 non-null float64\n",
      "max_leverage               1008 non-null float64\n",
      "net_leverage               1008 non-null float64\n",
      "orders                     1008 non-null object\n",
      "period_close               1008 non-null datetime64[ns, UTC]\n",
      "period_label               1008 non-null object\n",
      "period_open                1008 non-null datetime64[ns, UTC]\n",
      "pnl                        1008 non-null float64\n",
      "portfolio_value            1008 non-null float64\n",
      "positions                  1008 non-null object\n",
      "prices                     1008 non-null object\n",
      "returns                    1008 non-null float64\n",
      "sharpe                     1004 non-null float64\n",
      "short_exposure             1008 non-null float64\n",
      "short_value                1008 non-null float64\n",
      "shorts_count               1008 non-null int64\n",
      "sortino                    1004 non-null float64\n",
      "starting_cash              1008 non-null float64\n",
      "starting_exposure          1008 non-null float64\n",
      "starting_value             1008 non-null float64\n",
      "trading_days               1008 non-null int64\n",
      "transactions               1008 non-null object\n",
      "treasury_period_return     1008 non-null float64\n",
      "dtypes: datetime64[ns, UTC](2), float64(28), int64(3), object(6)\n",
      "memory usage: 315.0+ KB\n"
     ]
    }
   ],
   "source": [
    "backtest.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract pyfolio Inputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `extract_rets_pos_txn_from_zipline` utility provided by `pyfolio` extracts the data used to compute performance metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:10:49.441716Z",
     "start_time": "2020-06-17T19:10:48.382873Z"
    }
   },
   "outputs": [],
   "source": [
    "returns, positions, transactions = extract_rets_pos_txn_from_zipline(backtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Persist Results for use with `pyfolio`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:11:03.179302Z",
     "start_time": "2020-06-17T19:11:03.135781Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore('backtests.h5') as store:\n",
    "    store.put('returns/pf_opt', returns)\n",
    "    store.put('transactions/pf_opt', transactions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:11:06.034165Z",
     "start_time": "2020-06-17T19:11:05.971730Z"
    }
   },
   "outputs": [],
   "source": [
    "with pd.HDFStore('backtests.h5') as store:\n",
    "    returns_pf = store['returns/pf_opt']\n",
    "    tx_pf = store['transactions/pf_opt']\n",
    "    returns_ew = store['returns/equal_weight']\n",
    "    tx_ew = store['transactions/equal_weight']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:11:25.236161Z",
     "start_time": "2020-06-17T19:11:24.956131Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes= plt.subplots(nrows=2, figsize=(14,6))\n",
    "returns.add(1).cumprod().sub(1).plot(ax=axes[0], title='Cumulative Returns')\n",
    "transactions.groupby(transactions.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[1], title='Cumulative Transactions')\n",
    "sns.despine()\n",
    "fig.tight_layout();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-06-17T19:11:19.341135Z",
     "start_time": "2020-06-17T19:11:18.857155Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(16, 8), sharey='col')\n",
    "returns_ew.add(1).cumprod().sub(1).plot(ax=axes[0][0],\n",
    "                                        title='Cumulative Returns - Equal Weight')\n",
    "returns_pf.add(1).cumprod().sub(1).plot(ax=axes[1][0],\n",
    "                                        title='Cumulative Returns - Mean-Variance Optimization')\n",
    "tx_ew.groupby(tx_ew.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[0][1],\n",
    "                                                               title='Cumulative Transactions - Equal Weight')\n",
    "tx_pf.groupby(tx_pf.dt.dt.day).txn_dollars.sum().cumsum().plot(ax=axes[1][1],\n",
    "                                                               title='Cumulative Transactions - Mean-Variance Optimization')\n",
    "fig.suptitle('Equal Weight vs Mean-Variance Optimization', fontsize=16)\n",
    "sns.despine()\n",
    "fig.tight_layout()\n",
    "fig.subplots_adjust(top=.9)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:ml4t-zipline]",
   "language": "python",
   "name": "conda-env-ml4t-zipline-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.6"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": true,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "252.628px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
